As
immune checkpoint blockade and other immune-based therapy approaches lead to
broad treatment advances among patients with advanced cancer, an important
consideration is how to best select patients whose tumors will respond to these
therapies. As a consequence predictive and prognostic markers are needed. There
are genomic features, such as tumour mutation burden (TMB), microsatellite
instability (MSI), and immune phenotype features, such as programmed
death-ligand 1 (PD-L1), CTLA-4 and tumour infiltrating lymphocytes (TILs), to
predict response to immunotherapies (ITs). Several studies show the correlation
between TMB and predicted neoantigen load across multiple cancer types.
Response to immune checkpoint inhibitors is higher in tumours with high TMB. The
candidate biomarker that has been studied mostly other than TMB is PD-L1
expression in trials utilizing programmed cell death-1 (PD-1) blockade. PD-L1
and PD-1 expression are dynamic markers that change in relation to local
cytokines and other factors, and the thresholds that separate “positive” and “negative”
PD-L1 expressions remain under debate. PD-L1 expression is now a routine
diagnostic marker for patients with newly diagnosed NSCLC. The potential
applicability of PD-L1 in other disease settings is still uncertain. Microsatellite
instability is characterised by high rates of alterations to repetitive DNA sequences
caused by impaired mismatch repair (MMR); MSI was the biomarker was approved
according to tumor's initial location. Combining TMB with specific genomic alterations
is crucial. Moreover, new biomarkers are being investigated.
Keywords: Checkpoint inhibitor, Immunotherapy, MSI, PD-L1, PD1, Predictive , Prognostic , TIL, TMB.
